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Home / Jobs / Intelligence Factory (P26)

Data Engineer (India)

Intelligence Factory (P26)

Pune, Maharashtra, IN
Intelligence Factory (P26) logo

Role tags

FulltimeData scienceData Engineer

Tech stack mentioned

Python

Role overview

Formatting this description...

We're building foundational models for general purpose manipulation. Our data infrastructure allows us to generate rich, multi-modal human demonstration data at exponential scale. We are using this data to train general-purpose manipulation models that work reliably across tasks, objects, and robot embodiments. We are live in deployment across multiple verticals. As a data engineer, you'll architect the highest quality robotics dataset in the world - owning the pipelines that turn raw sensor data into the datasets our models train on. What you'll do: Build pipelines that turn raw multi-modal sensor data into training-ready datasets Build tooling for data exploration, filtering, versioning, and release management Implement quality checks that catch bad data before training Work in a tight feedback loop with the model team to improve data for training You should have: Strong Python and experience building data pipelines at scale Experience with multi-modal or time-series sensor data (video, IMU, force - any of these) Experience with data validation at scale - anomaly detection, distribution checks, or debugging corrupted data Proof of decision-making with incomplete information Our culture is built on honesty and willingness to fail fast. If you see yourself fitting here, please apply. Comp: ₹15L-₹40L Full-time, on-site in Pune We are developing foundational models for general purpose manipulation, trained on human demonstration data collected from our data factories – facilities where human data generators wear our data collection gloves and perform various tasks. We use this data to train custom models that generalize over tasks, objects and work on any robot hardware.

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LocationPune, Maharashtra, IN
TypeNot specified
SalaryINR 1500000 - 4000000
Apply byOpen

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